Hierarchical Agent-based Reinforcement Learning Framework for Automated Quality Assessment of Fetal Ultrasound Video

no code implementations • 14 Apr 2023 • Sijing Liu, Qilong Ying, Shuangchi He, Xin Yang, Dong Ni, Ruobing Huang

Ultrasound is the primary modality to examine fetal growth during pregnancy, while the image quality could be affected by various factors.

Sketch guided and progressive growing GAN for realistic and editable ultrasound image synthesis

no code implementations • 14 Apr 2022 • Jiamin Liang, Xin Yang, Yuhao Huang, Haoming Li, Shuangchi He, Xindi Hu, Zejian Chen, Wufeng Xue, Jun Cheng, Dong Ni

Our main contributions include: 1) we present the first work that can synthesize realistic B-mode US images with high-resolution and customized texture editing features; 2) to enhance structural details of generated images, we propose to introduce auxiliary sketch guidance into a conditional GAN.

Generative Adversarial Network Image Generation

Statistical Dependency Guided Contrastive Learning for Multiple Labeling in Prenatal Ultrasound

no code implementations • 11 Aug 2021 • Shuangchi He, Zehui Lin, Xin Yang, Chaoyu Chen, Jian Wang, Xue Shuang, Ziwei Deng, Qin Liu, Yan Cao, Xiduo Lu, Ruobing Huang, Nishant Ravikumar, Alejandro Frangi, Yuanji Zhang, Yi Xiong, Dong Ni

In this study, we build a novel multi-label learning (MLL) scheme to identify multiple standard planes and corresponding anatomical structures of fetus simultaneously.

Contrastive Learning Image Classification +3

Remove Appearance Shift for Ultrasound Image Segmentation via Fast and Universal Style Transfer

no code implementations • 14 Feb 2020 • Zhendong Liu, Xin Yang, Rui Gao, Shengfeng Liu, Haoran Dou, Shuangchi He, Yuhao Huang, Yankai Huang, Huanjia Luo, Yuanji Zhang, Yi Xiong, Dong Ni

In this paper, we propose a novel and intuitive framework to remove the appearance shift, and hence improve the generalization ability of DNNs.

Image Segmentation Semantic Segmentation +1